CN111813959B - Method for constructing knowledge graph of meteorological record file - Google Patents
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Abstract
The invention provides a method for constructing a weather record archive knowledge graph, which comprises the following steps: collecting relevant data in the field of weather record files; comprehensively analyzing main content of the weather record file, selecting basic terms, classification information and subject words in the weather record file field as concepts, and finishing the definition of commonly used concepts of query of the weather record file body; defining sub-concepts on the basis of the commonly used concepts to form a hierarchical structure of the concepts; defining each concept attribute and the value constraint of the attribute thereof, wherein the value constraint comprises the numerical attribute of the related content information of the concept and the object attribute of the association relation between the concepts; defining a relation, defining a relation between concepts and an association relation between the concepts and attributes, and constructing possible semantic relations among the ontology concepts of the weather record file to form a weather record file ontology model; the ontology model is described through an ontology description language OWL, and a concept-to-data process is realized.
Description
Technical Field
The invention relates to the fields of computer technology, weather and archives, in particular to a method for constructing a knowledge graph of a weather record archive.
Background
At present, a national weather system is built for 1 national weather archive and 31 provincial weather archives together, various weather record files starting from the middle of the 19 th century are stored and managed, and the files are basic data for researching the modern climate change and environmental evolution irreplaceable in China and are important scientific and technological information resources in China.
The digital weather archive test point construction is carried out by four weather archives of China weather bureau organizations, namely Anhui, hebei, shandong and Hubei from 2018, wherein one important test point construction content is to establish a high-quality digital weather archive management system construction for the national weather archives, and the mining algorithm of a background of the digital weather archive management system and the analysis effect of related statistical query directly depend on the quality of a background knowledge base, so that the establishment of the high-quality weather archive knowledge base has urgent requirements.
Disclosure of Invention
The invention aims to provide a method for constructing a weather record file knowledge graph so as to meet the requirement of establishing a high-quality weather record file knowledge base.
In order to solve the technical problems, the invention provides a method for constructing a weather record file knowledge graph, which comprises the following steps:
Collecting relevant data in the field of weather record files;
comprehensively analyzing the content of the weather record file data, selecting basic terms, classification information and subject words in the weather record file field as concepts, and finishing the definition of commonly used concepts of query of the weather record file body;
defining sub-concepts on the basis of the query common concepts to form a hierarchical structure of concepts;
defining each concept attribute and the value constraint of the attribute thereof, wherein the value constraint comprises the numerical attribute of the related content information of the concept and the object attribute of the association relation between the concepts;
defining a relation, defining a relation between concepts and an association relation between the concepts and attributes, and constructing possible semantic relations among the ontology concepts of the weather record file to form a weather record file ontology model;
the ontology model is described through an ontology description language OWL, and a concept-to-data process is realized.
Optionally, in the method for constructing a weather record file knowledge graph, the method for constructing a weather record file knowledge graph further includes:
based on the theory of ontology, combining archives and meteorological knowledge to complete the establishment of an ontology model in the field of meteorological record archives;
The theory of the body includes:
the field and the range of the weather record file body are clearly constructed;
analyzing the possibility of the existing ontology in the field of multiplexing weather record files;
acquiring knowledge in the field of meteorological record files;
determining a query common concept in the field of weather record files;
establishing a hierarchy of query common concepts in the field of weather record files;
defining attributes and constraints among query common concepts in the field of weather record files;
instantiating the constructed weather record file body;
judging whether logic reasoning and detection are carried out, if so, returning to the step of determining the common concept of query in the field of weather record files;
otherwise, updating the body of the constructed weather record file, and returning to the step of acquiring the knowledge in the field of the weather record file.
Optionally, in the method for constructing a weather record file knowledge graph, the method for constructing a weather record file knowledge graph ontology model further includes:
the field and the range of the constructed weather record file body are documented;
the possibility of multiplexing the existing ontology in the weather record archive field is documented;
the method comprises the steps of documenting a query common concept in the field of weather record files;
The method comprises the steps of documenting a hierarchy of query common concepts in the field of weather record files;
the attribute and the constraint among the commonly used concepts in the field of weather record files are documented;
documentation is carried out on the constructed instance of the weather record archive body;
the method comprises the steps of documenting the update of a constructed weather record archive body;
the document formed by the operation of documentation is used in the subsequent steps.
Optionally, in the method for constructing a knowledge graph of a weather record file, the relevant data in the weather record file field includes acquired metadata of a weather archive, metadata of a weather archive category, metadata of a weather archive file, metadata of a file in the weather archive and metadata of weather archive management;
the related data in the meteorological record file field also comprises queried ground files, high altitude files, radiation files, agricultural files, acid rain files, weather map files and station history leather files for automatic word list supplement;
the related data in the weather record file field also comprises data acquired based on the technical specifications of weather file business issued by the China weather office.
Optionally, in the method for constructing a knowledge graph of a weather record file, by analyzing the search requirement and the data of the weather record file, starting from the problem of difficulty in searching the weather record file, three aspects of weather record file files, file formation and archive management of the file are defined, and the common search concepts of the weather observation file, time, weather archive, weather record file files, administrative areas, file formation units, weather observation elements and the like, which can quickly search for the positioning file, are extended based on the common search concepts, such as a management system, a responsible person, a production unit, a weather observation specification, a weather observation instrument and a weather observation method;
The value constraint defining each concept attribute and the attribute thereof comprises defining a paper file attribute, an electronic file attribute, an administrative region attribute, a weather observation station attribute, a weather observation event attribute, a time attribute, a weather observation liability person attribute, a weather observation standard attribute, a weather observation element attribute, a weather observation instrument attribute, a weather observation method attribute, an observation record attribute, a weather archive attribute, a archive formation unit attribute, a weather record archive attribute and a weather archive management regulation attribute.
Optionally, in the method for constructing a knowledge graph of a weather record file, the definition of the ontology relationship of the weather record file is based on business analysis of the weather record file, and the method uses the weather record file itself, i.e. "weather observation file", as a core to define the relationship between concepts so as to establish the relationship between the data of the weather record file.
Optionally, in the method for constructing the weather record file knowledge graph, the weather record file data is researched to obtain weather observation files of different types at the same place and at the same time, wherein the weather observation files have an association relationship;
Different types of weather-observation files include: the most primitive observation records of the gas book and the self-recording paper, the observation data in the gas book read from the self-recording paper, the data in the gas meter read from the gas book, the month statistics calculated based on the day observation data, the data in the year report read from the month report, and the year statistics calculated based on the month statistics.
Optionally, in the method for constructing a weather record file knowledge graph, the weather record file knowledge graph includes an intelligent retrieval module based on a file itself, an intelligent retrieval module based on an observation element, and an intelligent retrieval module based on an observation station, wherein:
the intelligent retrieval module based on the archives is used for searching main meteorological record archives in the current archives in a correlation way based on conceptual relations and entity relations of the knowledge graph of the meteorological record archives, then associating storage positions, observation stations, formation time, places, observation elements and the like of each archive, and establishing a relation network for different entities related to the archives;
the intelligent retrieval module based on the observation elements is used for searching files in an associated mode according to a knowledge association relation network of the observation elements and based on the air pressure, air temperature, humidity and precipitation observation elements, the data characteristics of the file records are marked on the relation between the file files and the observation elements, and meanwhile observation times, observation persons, observation stations and files where the observation persons, the observation stations and the observation files are located are associated;
The intelligent retrieval module based on the observation station searches out image files, observation records, observers, station lengths, observation elements, observation instruments, change matters and observation field environment information of a certain period of the station or searches the station of the observation instrument used in the past according to the association relation network of the observation station to form a station leather information network.
According to the method for constructing the knowledge graph of the weather record file, ontology model construction of the weather record file field is completed by combining archives and weather knowledge based on ontology theory, the field and range of the established ontology are clearly established, the possibility of multiplexing the existing ontology in the field is analyzed, the knowledge of the field is obtained, the common query concepts of the field are determined, the hierarchy of the common query concepts of the field is established, the attribute and the constraint among the common query concepts of the field are defined, the established ontology is instantiated, whether logical reasoning and detection are carried out or not is judged, if yes, the established ontology is returned to the step of determining the common query concepts of the field, otherwise, the established ontology is updated, and the step of obtaining the knowledge of the field is returned to, so that the knowledge graph can be constructed by utilizing the body to effectively organize the data of the weather record file in a top-down mode.
Drawings
FIG. 1 is a schematic diagram of an ontology model construction process according to another embodiment of the present invention;
FIG. 2 is a conceptual hierarchy diagram of an ontology according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of a query common concept relationship according to another embodiment of the present invention;
FIG. 4 is a conceptual relational hierarchy diagram of another embodiment of the invention;
FIG. 5 is a schematic diagram of an ontology concept relationship according to another embodiment of the present invention;
FIG. 6 is a diagram illustrating an ontology-entity mapping relationship according to another embodiment of the present invention;
FIG. 7 is a conceptual hierarchy of a meteorological observation archive according to another embodiment of the present invention;
FIG. 8 is a conceptual hierarchy of weather record files according to another embodiment of the present invention;
FIG. 9 is a conceptual hierarchy of weather record archive management according to another embodiment of the present invention;
FIG. 10 is a schematic diagram of a weather record file association relationship according to another embodiment of the present invention;
FIG. 11 is a schematic diagram of an association relationship between elements of a weather record file according to another embodiment of the present invention.
Detailed Description
The method for constructing the knowledge graph of the weather record file provided by the invention is further described in detail below with reference to the accompanying drawings and specific embodiments. Advantages and features of the invention will become more apparent from the following description and from the claims. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the invention.
The core idea of the invention is to provide a method for constructing a weather record file knowledge graph so as to meet the requirement of establishing a high-quality weather record file knowledge base.
In order to achieve the above-mentioned idea, the present invention provides a method for constructing a knowledge graph of a weather record file, which comprises: collecting weather record archive data; comprehensively analyzing the content of the weather record file data, selecting basic terms, classification information and subject words in the weather record file field as concepts, and finishing the definition of the commonly used concepts of the query of the weather record file body; defining sub-concepts on the basis of the query common concepts to form a hierarchical structure of concepts; defining each concept attribute and the value constraint of the attribute thereof, wherein the value constraint comprises the numerical attribute of the related content information of the concept and the object attribute of the association relation between the concepts; defining a relation, defining a relation between concepts and an association relation between the concepts and attributes, and constructing possible semantic relations among the ontology concepts of the weather record file to form a weather record file ontology model; the ontology model is described through an ontology description language OWL, and a concept-to-data process is realized.
The embodiment also provides a method for constructing a weather record file knowledge graph, which comprises the following steps: based on the theory of ontology, combining archives and meteorological knowledge to complete the establishment of an ontology model in the field of meteorological record archives; the theory of the body includes: the field and the range of the weather record file body are clearly constructed; analyzing the possibility of the existing ontology in the field of multiplexing weather record files; acquiring knowledge in the field of meteorological record files; determining a query common concept in the field of weather record files; establishing a hierarchy of query common concepts in the field of weather record files; defining attributes and constraints among query common concepts in the field of weather record files; instantiating the constructed weather record file body; judging whether logic reasoning and detection are carried out, if so, returning to the step of determining the common concept of query in the field of weather record files; otherwise, updating the body of the constructed weather record file, and returning to the step of acquiring the knowledge in the field of the weather record file.
The embodiment provides a weather record archives knowledge graph construction system, the weather record archives knowledge graph includes: a weather record archive ontology concept definition module configured to define an ontology concept based on primary weather record archive resources, standards and specifications; a weather record archive ontology attribute definition module configured to define ontology attributes based on primary weather record archive resources, standards and specifications; an ontology concept relationship definition module configured to define a relationship between the ontology concepts and the ontology attributes; the ontology language representation module is configured to describe the ontology concepts through OWL language and to dataize the ontology concepts so that a machine can understand and process the ontology concepts; the ontology and entity mapping module is configured to import a large number of multi-source heterogeneous weather record archive data acquired through a knowledge graph construction technology into a weather record archive ontology framework model to acquire entities, attributes and relations from the multi-source heterogeneous weather record archive data, so that the whole construction of the weather record archive knowledge graph is completed.
The data resource of the meteorological record file is the basis for constructing a knowledge graph, and deep analysis of the characteristics and the source composition of the data is a necessary condition for construction. Based on cognition of meteorology and archives, on the basis of combing multisource heterogeneous meteorological record archival data collected by the existing Anhui province meteorological office, more and more comprehensive meteorological record archival knowledge is obtained by combining meteorological archival standards, business specifications and the like, and knowledge sources and knowledge acquisition methods are open and can supplement knowledge and self-evolve knowledge according to new knowledge sources. The current realized knowledge acquisition mode of the weather archive knowledge graph mainly comprises the following aspects: the metadata of the weather record archives is formulated based on the national digital weather archives construction technology group and mainly comprises weather archives metadata, weather archives category metadata, weather archives metadata, file metadata in the weather archives and weather archives management metadata 5 major metadata.
The metadata of the weather archive stores basic information of the archive in a structured form in a relational database, and mainly comprises archive numbers, archive codes, archive names, aliases, english names, levels, service ranges, archive types, archive numbers, earliest archive types, earliest archive ages, archive construction time, relocation conditions, current archive areas, archive storage conditions, archive environments, geographic positions, supporting facilities, access levels and the like.
The metadata of the weather archive category is stored in a relational database in a structured form, and comprises archive classification codes, category names, category definitions, category names, short names, starting time, ending time, archive sources, arrangement modes, archive case numbers, album numbers, number of pieces, page numbers, grouping modes, informatization conditions, discharge positions, content, archive media and other contents.
The metadata of the weather archive files is stored in a relational database in a structured form, and the basic condition of each archive file comprises an archive number, a registration date, a file number, a region number, a class number, a serial number, a name, a subject term, a production unit, a year, the number of pieces, the number of pages, a secret level, a publishing date, a term, a borrowing or borrowing condition, a cabinet number, remarks, whether the change condition exists or not and a digital condition.
The in-file is the minimum unit for forming the file entity, and the file is generally composed of a plurality of files with the same time, region and element, and the metadata of the in-file in the weather file is used for describing the number of the file, the serial number in the file, the number of the file, the file name, the subject word, the file generation unit, the formation date, the page number, the change condition, the storage position, the remark and the like.
Meteorological archive management metadata stores metadata of management procedures such as handover, arrangement, borrowing, modification, authentication and the like of archives. The file management system mainly comprises file transfer application data, file receiving data, file arrangement data, file borrowing application data, file borrowing approval data, file returning application data, file returning processing data, file identification data, file change data, file checking and backup data, file retrieval data and the like.
7 types of files such as ground, high altitude, radiation, agriculture, acid rain, weather patterns, station history and leather files are directly searched by entering the restaurant, and automatic supplement and improvement of word list are carried out.
The ground observation files collected in the prior art mainly comprise paper files and electronic files.
The paper files mainly comprise ground weather observation self-recording paper (called self-recording paper for short), a ground weather observation record book (gas book-1), a weather report observation record book (gas book-2) and other auxiliary observation books, a ground weather record month report, a ground weather record year report (gas meter-21) and the like. Wherein the self-recording paper reflects the change trend of the observed data in a period of time; the gas book records observation data of different observation times in natural days; the month report records the observation data of natural months from day to day and the statistical data of month average, month total, month highest, month lowest and the like; the year report records the natural year month-by-month observation data, and the year average, the year total, the year highest, the year lowest and other statistical data.
The electronic files comprise data observation electronic files and paper scanning electronic files generated by the ground automatic weather station.
The high-altitude observation files collected at present comprise high-altitude paper observation files and electronic files.
The paper observation file comprises a high-altitude meteorological observation record table (called a high table for short), and the high-altitude meteorological observation record table is recorded by moon high altitude wind measurement, temperature, humidity, air pressure and the like.
The electronic files comprise data observation files generated by the high-altitude automatic weather station and electronic scanning pieces of various paper high-level tables.
The current collected meteorological radiation record files are divided into paper files and electronic files.
The paper file mainly comprises a meteorological radiation observation book, a meteorological radiation recording month report (gas meter-33) and the like, and the radiation observation book records radiation observation data; the radiation meter records month statistics such as full month radiation observation data, month average, month total, month highest, month lowest and the like.
The electronic files comprise data observation electronic files generated by the automatic radiation weather station, various radiation gas books and various radiation month report paper scanning files.
The current collected agricultural meteorological record files are divided into paper observation files and electronic files.
The paper observation files comprise an agricultural meteorological observation book and an agricultural meteorological observation record chronology, wherein the agricultural meteorological observation book mainly comprises an agricultural qi book-1 (crop growth condition observation book), an agricultural qi book-2 (soil moisture observation book), an agricultural qi book-3 (natural meteorological observation book), an agricultural qi book-4 (livestock meteorological observation record book) and the like. The agricultural meteorological observation annual report mainly comprises an agricultural gas meter-1 (crop growth condition observation annual report), an agricultural gas meter-2 (soil moisture observation annual report), an agricultural gas meter-3 (natural weather observation annual report), an agricultural gas meter-4 (livestock meteorological observation annual report), an agricultural gas meter-5, an agricultural gas meter-6, an agricultural gas meter-7, an agricultural gas meter-8 and the like.
The electronic files comprise data observation files generated by an automatic agricultural meteorological observation station and various agricultural gas meters and agricultural gas thin paper scanning files.
The current collection of acid rain weather record files comprises paper observation files and electronic files, wherein the paper observation files are divided into an acid rain observation record book (special book-1) and an acid rain observation record month report (special table-1).
The electronic files comprise various paper acid rain month reports, electronic scanning files of an acid rain observation book and data observation electronic files generated by an acid rain observation station.
The weather diagrams collected at present mainly comprise paper files and electronic scanning files, and the weather diagrams mainly comprise ground weather diagrams, high altitude weather diagrams and the like.
The station history leather file comprises a weather station history leather data file and a station history image file. The station history leather file records station history leather data, records change records of the attributes of a meteorological observation station, such as station names, station levels, station positions, observation elements, observation instruments, observation time systems, observation specifications, station environments and the like, and is a data foundation of station culture construction.
The station image file is used for recording the archived image (including photo) files of environments, instruments and the like related to weather station histories.
And collecting various notifications and technical specifications of weather files issued by the Chinese weather bureau, expanding various word lists of the weather files by using a natural language processing technology, and discovering the relationship among nodes in a knowledge graph based on a data mining technology. Including the line standard, national standard, landmark and business technical specification issued by the China weather exchange. The method mainly comprises the steps of Meteorological file classification and coding, meteorological record file management regulation, paper Meteorological record file arrangement regulation, meteorological file metadata, meteorological data set description document format, ground Meteorological observation data file and record book form, meteorological data archiving format ground, ground Meteorological observation regulation, regular high-altitude image observation service regulation, high-altitude image observation data format, acid rain observation regulation, acid rain Meteorological observation data format, agricultural Meteorological observation regulation, meteorological data archiving format-automatic observation soil moisture, and the like.
Aiming at a large amount of literature data of the weather files, the template-based weather file knowledge extraction is researched and realized, the knowledge of the knowledge graph is supplemented, and the weather file knowledge automatic extraction technology driven by the knowledge graph is researched.
And developing a plurality of weather archive knowledge service applications, and correcting and supplementing knowledge of the knowledge graph based on application feedback of a user. With the continuous enhancement of application services, this part will be an important knowledge source of knowledge patterns of future weather record files.
In the weather record archive knowledge graph body model provided in this embodiment, the weather record archive knowledge graph body model system includes an intelligent retrieval module based on the archive itself, an intelligent retrieval module based on the observation element, and an intelligent retrieval module based on the observation station, wherein: when a user queries files, only general query directions are possible, specific query targets are not clear, a system is required to comprehensively know files in the file collection, and a desired specific file is queried to form a query list. As shown in FIG. 2, based on the conceptual relation and entity relation of the weather record file knowledge graph, 8 types of files such as a ground weather observation book, a self-recording paper, a ground weather observation month report, a ground weather year report, a weather chart, a station history, a college, a photo file and the like are searched in a current archive in an associated manner, then each file storage position, an observation station, formation time, places, observation elements and the like are associated, a relational network is established for different entities related to the files, and the relationship is displayed in a graph form, so that a user knows which files are stored in the archive from the upper layer first, and then views the association relation of the files, an intelligent inquiry mode of files from large to small and top to bottom is provided for the user, the retrieval accuracy and breadth are enlarged, and the file searching requirements of the user are met to the greatest extent.
In practical business applications, a user may need to query a specific observation element-related profile to obtain the coming and going pulses of that element based on certain business needs.
As shown in fig. 10, by means of the knowledge association relationship network of the observation elements, based on the 4 observation elements of air pressure, air temperature, humidity and precipitation, the files such as the self-recording paper, the ground weather observation book and the month report form of Dangshan county in 1959 in 1 month and 15 are found in association, the data characteristics of the file records are marked on the relationship between the files and the observation elements, and meanwhile, the time, the observer, the observation station, the files in which the user is located and the like are associated, and after analyzing the file characteristics, the user obtains the file wanted by the user.
The historical record of the station history records the station name, station level, station position, observation elements, observation instrument, observation time system, observation standard, station environment and other attributes of the weather observation station, and is an important basis for reflecting the long-term change development of the station. At present, the historical relic files of the station are stored in the form of TXT text files, and can not be searched and inquired efficiently. For example, a user wants to query information such as a station length, an observation field environment, an observation instrument, an observation file, etc. of a certain station in a certain year, and a conventional searching method needs to consume a lot of time.
By means of the association relation network of the observation station, information such as image files, observation records, observers, station lengths, observation elements, observation instruments, change matters, observation field environments and the like of the station in a certain period can be searched, and in turn, the fact that the stations using certain observation instruments in the past are available can be also searched, the information of the stations along the leather is displayed in a graph mode, a user is helped to quickly know the information of the stations along the leather, and meanwhile data support is provided for future station culture construction (see figure 11).
Based on the theory of ontology, the ontology model construction in the field of meteorological records is completed by combining the archives and the knowledge in the aspect of meteorology. Firstly, collecting relevant data in the field of weather record files, comprehensively analyzing main content of the weather record files, finishing definition of query common concepts of weather record file bodies, defining sub-concepts on the basis of the query common concepts to form a hierarchical structure of the concepts, and then defining concept attributes and value constraints of the attribute. And then, constructing possible semantic relations among ontology concepts of the weather record file to form an ontology model. Finally, describing the ontology model through an ontology description language OWL, realizing a process from concept to data, and laying a foundation for knowledge acquisition (see FIG. 1).
The basic flow of the meteorological record archive ontology model construction comprises 5 steps,
1) Ontology definition an ontology is defined based on the primary weather record archive resources, standards and specifications.
2) Ontology attribute definition: the ontology attributes are defined based on the primary weather record archive resources, standards and specifications.
3) Ontology concept relationship definition: an ontology concept and a relationship between concepts are defined.
4) Ontology language representation: the ontology representation adopts the OWL language, and the concepts are dataized through the description of the OWL language on the ontology, so that the machine can understand and process.
5) Ontology and entity mapping: a large amount of multi-source heterogeneous weather record file data obtained through a knowledge graph construction technology is imported into a weather record file body frame model, and the entity, the attribute and the relation are obtained from the multi-source heterogeneous weather record file data, so that the integral construction of the weather record file knowledge graph is completed.
The weather record archive ontology concept definition comprises: by analyzing the requirement and the data of the weather record files, starting from the problem of difficult searching of the weather record files, the method comprises the steps of defining the common searching concepts of the weather observation files, time, weather archives, weather record files, administrative areas, file forming units, weather observation elements and the like, which can quickly search for the positioning files, and constructing the body concept hierarchical structure chart 2 based on the concepts of the management systems, the responsibilities, the production units, the weather observation specifications, the weather observation instruments, the weather observation methods and the like. The relationship of the query common concept such as the query common concept weather observation file, weather archive, weather record archive, administrative area, weather observation station, time and the like is shown in fig. 3.
The main meteorological record files collected in the current Anhui province meteorological archives can be divided into 7 types of files such as ground, high altitude, radiation, agriculture, acid rain, weather patterns, station historic and the like, and each type of file is divided into multiple types according to different observation elements, observation time and observation data. The conceptual hierarchy of the weather-observing archive is shown in FIG. 7, the weather-recording archive forming conceptual hierarchy is shown in FIG. 8, and the weather-recording archive management conceptual hierarchy is shown in FIG. 9.
The weather record archive body attribute definition includes: by researching the search requirement of a user on the paper file of the weather record file, the paper file, the electronic file and the metadata of the weather record file are checked and analyzed, and words which can represent the characteristics of the weather observation file and can meet the requirement of the user on quickly searching the positioning file are selected as attributes. The method comprises the following steps of: station number, file name, file number, formation unit, region number, formation date, record type, storage period, keyword, security class, and the like.
By researching the searching requirement of a user on the electronic file of the file, the electronic file of the meteorological record file is checked and analyzed, and words which can represent the characteristics of the electronic file and can meet the requirement of the user on quickly searching and positioning the electronic file are selected as attributes. The method comprises the following steps of: station number, formation unit, file name, region number, formation date, file type, record type, keyword, security class, server address, file path, observer, file editor, file auditor, etc.
The weather record file formation includes: administrative region attribute definition: the administrative region selects a region name and a region code as attributes. Weather observation station attributes: the meteorological observation station selects the station name, station position, station level, zone station number, surrounding barriers of the station, affiliated institutions and other attributes. Meteorological observation events define attributes such as event type, event name, event description, start time, end time, etc. The time attribute defines the attribute of selecting time type, date, etc. The attribute definition of the weather observation responsibilities selects attributes such as responsibilities, names, units where the weather observation responsibilities are located, and the like. Meteorological observation Specification attributes define attributes such as "Specification type", "Specification name", "drafting time", "drafting Unit", "drafting person", and the like. The meteorological observation element attribute selects the attributes such as element code, element name, element alias and the like. The weather observation instrument attribute selects the instrument name, instrument distance and height, instrument model, instrument manufacturer and other attributes. Meteorological observation method attributes define attributes such as "method name".
The content of the observation record is the observation values of different observation elements, different times and different statistical dimensions, and the attribute definition adopts a mode of combining time + elements and dimension + elements so as to clearly and comprehensively display the observation data of a certain place at a certain time. The attributes contained in the different types of observation records are different, and the attributes of each type of observation record are defined below.
The ground observation records can be divided into annual observation records, monthly observation records, daily observation records and the like according to the time dimension. The observation time and the observation factors of the ground observation station can change along with the development of the station, the observation time and the observation factors of different stations and different ages can be different, the observation factors are various, and the ground observation factors commonly used and the observation time of a certain station in a certain year are exemplified below to define the attribute.
The attributes of the observation records of a specific day are selected as defined below, and the attributes of the air temperature, the air pressure, the precipitation amount, and the like, such as 01 time, 07 time, 13 time, 19 time, and the like, are defined so as to store the observation value of a certain element at a certain time at a certain place.
The weather archives select the attributes such as the archives name, english name, archives number, alias, business scope, current archives area, the types of files collected, the affiliated institutions, the archives codes, the geographic position, the number of files collected and the like. The file forms the attributes of selecting unit names, unit places and the like.
The file files are selected from file names, file codes, standard names, classification numbers, region numbers, formation units, ages, start dates, end dates, file numbers, zone station numbers, subject words, file organization mode, page numbers, security classes, storage time periods, storage positions, receivers, transfer persons and the like.
Meteorological record archive management regulation defines attributes such as 'regulation name', 'issuing time', 'transmission number', and the like.
The definition of the ontology concept relationship comprises the following steps: in the weather record archive body, according to the hierarchy and structure of the body relation, the obtained relation mainly comprises the following six major categories, namely: physical, spatial, management, observation, temporal and event correlation (see fig. 4).
The relation between the 'concepts' of the weather record file body is to connect the 'concepts' to form an important part with relevant frame. The definition of the relationship is a core element for constructing a weather record archive knowledge system and also provides a direction for later knowledge acquisition. The definition of the body relation of the weather record files is to define the relation among concepts by taking the weather record files, namely 'weather observation files', as a core around the production, management and utilization of the weather record files according to the business analysis of the weather record files so as to establish the relation among the weather record file data. The general conceptual relationship diagram is shown in fig. 5:
based on the historical and leather-based data of the meteorological observation station, concepts such as station length, station environment images, instrument images used by the station, station historical change matters and the like of the meteorological observation station are dug, and the association relationship between the station and the station is constructed, so that the multidimensional information of a certain time point of the station can be displayed at the same time, and a user can acquire the station information more accurately, intelligently and conveniently.
Through investigation of weather record archival data, association relations exist between different types of weather observation files at the same place and at the same time, for example, in a ground weather observation file, an air book and self-recording paper are the most original observation records, the observation data in the air book can be read from the self-recording paper, the data in a gas meter (month report) is read from the air book and recorded, month statistics are calculated based on the day observation data, the data in a year report is read from the month report, and year statistics are calculated based on the month statistics. The ground, weather, radiation, agriculture and acid rain respectively comprise different types of weather record files, each type of weather record file comprises different earth observation elements, and the files have mutual association relations. The relationship between the weather record files of the same time and the same place has the relationship of data progressive among the weather record files of different time dimensions, the observation data of self-recording paper can be extracted into a gas book, the data in the gas book is recorded into a month report form through statistical processing, and the data in the month report form is recorded into a year report form through statistical processing. Various paper weather archive files generate picture scanning pieces through a scanning technology. When a user inquires a certain archive according to time and place, the user can inquire various weather record files, and the user is helped to find the archive file which is more in line with the searching intention based on the file attribute and the association relation between the files.
One station can observe ground weather and high altitude weather, and the observation station can form ground and high altitude observation records at the same time and at the same place, so that a ground observation file and a high altitude observation file can be associated in a station+time mode and a place+time mode.
The ground observation file comprises self-recording paper, an air book and a gas meter, the change trend of observation data in a period of time is reflected, the ground observation file is a graph, the observation file is the observation record with the most original and the finest time granularity, the air book records the observation data with different times per day, the month observation data and the year observation data recorded by the gas meter can be divided into month report forms and year report forms, the month report forms record the daily observation data and month statistics data, and the year report forms record the month statistics data and year statistics data. By browsing and researching the files, the data dependency relationship among the files according to the time granularity is obtained, the data among the files have the association relationship, for example, the sunlight data of the gas book-1 is derived from sunlight self-recording paper, the daily observation data in the gas meter-1 is derived from the gas book, the month statistical data in the gas meter-21 is derived from the gas book-21, the data dependency relationship among the files is built, the data characteristics of the observation files are reflected, and a user can quickly search and locate the files which want to be searched.
The self-recording paper comprises air temperature self-recording paper, air pressure self-recording paper, wind direction and wind speed self-recording paper, precipitation self-recording paper, humidity self-recording paper and sunshine self-recording paper.
Business knowledge used in the work of the investigation weather business personnel knows that the correlation between partial ground observation weather elements is strong, and the numerical value of partial ground observation elements is calculated based on the values of other observation elements. For example precipitation, it may be associated with other elements: relative humidity, weather phenomenon, clouds, temperature, insolation, etc. If precipitation occurs (there is precipitation): the relevant observation elements will vary: the relative humidity value is higher, the weather phenomenon records the rainfall weather phenomenon, clouds (cloud amount > 0) exist, and the sunshine hours are relatively less or no sunshine exists. Taking air temperature as an example, other factors may be linked: weather phenomenon (icing, frost), precipitation, ground temperature, grass temperature, etc. If the air temperature is lower than 0℃: the relevant observation elements will vary: the ground temperature is lower, and the grass surface temperature is lower, and icing, frost and the like can possibly occur. Taking the example of high winds, one can correlate to other factors: wind speed, weather phenomenon (fog, haze, dew, frost). If the weather phenomenon of strong wind occurs: the relevant observation elements will vary: the maximum wind speed is more than or equal to 17m/s, and the possibility of weather phenomena such as big fog, haze, dew, frost and the like is small. Taking ground temperature as an example, it may be linked to other factors: frozen soil, weather phenomenon, etc. If the ground temperature of 5cm is lower than 0℃: the relevant observation elements will vary: frozen earth, ice, frost, etc. may be generated. The high-altitude meteorological record archive sounding (P3-049) observation record list, high-altitude list-11, high-altitude list-12, high-altitude list-13, high-altitude list-14 and high-altitude list-16 have no data dependency relationship, and are all independent observation records.
Indirect association relation exists among all types of high-altitude observation files, and further reasoning analysis is needed. Taking high-altitude wind observation records as an example, the high-altitude meter-11 and the high-altitude meter-12 are only different in used observation instruments, so that the high-altitude wind observation records and the high-altitude wind observation records can be related through observation elements.
The weather radiation record observation file comprises a paper gas meter-33 and an electronic file R file. Since the gas meter-33 and the R file each record the observed value of the same element in a certain place, the two can be related by time and the observed element.
The agricultural weather record archive mainly includes a paper agricultural gas book-1 (crop fertility status observation record book), an agricultural gas book-2 (soil humidity measurement record book), an agricultural gas book-3 (natural weather observation record book), an agricultural gas book-4 (livestock weather observation record book), an agricultural gas meter-1 (crop fertility status observation record table), an agricultural gas meter-2 (soil humidity measurement record table), an agricultural gas meter-3 (weather observation record table), an agricultural gas meter-3 (livestock weather observation record table) and the like, and the electronic files include an N file and a C file.
The ontology representation adopts the OWL language, and the concepts are dataized through the description of the OWL language on the ontology, so that the machine can understand and process. The OWL language describes the ontology in the form of triples: describing the upper and lower levels of the father-son concept; describing concepts and relationships among the concepts; description of attributes of concepts.
The mapping relationship between the ontology and the entity is illustrated in fig. 6: in the knowledge graph, the entity is the most basic element, the entity represents an objectively existing object, for example, the Dangshan weather observation station is an entity, which is a node of the graph in the knowledge graph, and the relationship between the entities is the connection line between the nodes in the graph. An ontology concept is an abstract description of an entity, there is a correspondence between the two, and adding an instance to an ontology concept is commonly referred to as ontology filling. The ontology filling is carried out after the ontology model is built, concepts, concept attributes and concept relations are defined firstly, and then examples are added for the defined concepts and concept relations to form a weather record archive entity relation model.
The above-described embodiments are provided as computer program products that may include one or more machine-readable media having stored thereon machine-executable instructions that, when executed by one or more machines, such as a computer, computer network, or other electronic device, may result in the one or more machines performing operations in accordance with embodiments of the present invention. The machine-readable medium may include, but is not limited to, floppy diskettes, optical disks, CD-ROMs (compact disk read-only memory), and magneto-optical disks, ROMs (read-only memory), RAMs (random access memory), EPROMs (erasable programmable read-only memory), EEPROMs (electrically erasable programmable read-only memory), magnetic or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing machine-executable instructions.
Furthermore, embodiments may be downloaded as a computer program product, wherein the program may be transferred from a remote computer (e.g., a server) to a requesting computer (e.g., a client) by way of one or more data signals embodied in and/or modulated by a carrier wave or other propagation medium via a communication link (e.g., a modem and/or network connection). Accordingly, a machine-readable medium as used herein may include, but is not required to, such a carrier wave.
In summary, the foregoing embodiments describe in detail different configurations of the knowledge graph body model of the weather record file and the construction method thereof, and of course, the present invention includes, but is not limited to, the configurations listed in the foregoing embodiments, and any contents of transformation based on the configurations provided in the foregoing embodiments fall within the scope of protection of the present invention. One skilled in the art can recognize that the above embodiments are illustrative.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, the description is relatively simple because of corresponding to the method disclosed in the embodiment, and the relevant points refer to the description of the method section.
The above description is only illustrative of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention, and any alterations and modifications made by those skilled in the art based on the above disclosure shall fall within the scope of the appended claims.
Claims (7)
1. The method for constructing the weather record file knowledge graph is characterized by comprising the following steps of:
based on the theory of ontology, combining archives and meteorological knowledge to complete the construction of a meteorological record archive ontology model;
the theory of the body includes:
the field and the range of the weather record file body are clearly constructed;
analyzing the possibility of the existing ontology in the field of multiplexing weather record files;
acquiring knowledge in the field of meteorological record files;
determining a query common concept in the field of weather record files;
establishing a hierarchy of query common concepts in the field of weather record files;
defining attributes and constraints among query common concepts in the field of weather record files;
instantiating the constructed weather record file body;
judging whether logic reasoning and detection are carried out, if so, returning to the step of determining the common concept of query in the field of weather record files;
Otherwise, updating the constructed weather record file body, and returning to the step of acquiring the knowledge in the field of the weather record file;
collecting weather record archive data;
comprehensively analyzing the content of the weather record file data, selecting basic terms, classification information and subject words in the weather record file field as concepts, and finishing the definition of the commonly used concepts of the query of the weather record file body;
defining sub-concepts on the basis of the query common concepts to form a hierarchical structure of concepts;
defining each concept attribute and the value constraint of the attribute thereof, wherein the value constraint comprises the numerical attribute of the related content information of the concept and the object attribute of the association relation between the concepts;
defining a relation, defining a relation between concepts and an association relation between the concepts and attributes, and constructing possible semantic relations among the ontology concepts of the weather record file to form a weather record file ontology model;
describing the ontology model through an ontology description language OWL, and realizing a process from concept to data;
the ontology concept and entity mapping are used for adding corresponding entities for the ontology concept, the correspondence of the concept-entity is completed, a large amount of multi-source heterogeneous weather record archive data obtained through a knowledge graph construction technology is imported into a weather record archive ontology framework model, and the entity, the attribute and the relation are obtained from the multi-source heterogeneous weather record archive data, so that the integral construction of the weather record archive knowledge graph is completed.
2. The method for constructing a knowledge graph of a weather record file according to claim 1, further comprising:
the field and the range of the constructed weather record file body are documented;
the possibility of multiplexing the existing ontology in the weather record archive field is documented;
the method comprises the steps of documenting a query common concept in the field of weather record files;
the method comprises the steps of documenting a hierarchy of query common concepts in the field of weather record files;
the attribute and the constraint among the commonly used concepts in the field of weather record files are documented;
documentation is carried out on the constructed instance of the weather record archive body;
the method comprises the steps of documenting the update of a constructed weather record archive body;
the document formed by the operation of documentation is used in the subsequent steps.
3. The method of claim 1, wherein the weather record file knowledge graph construction method comprises the steps of obtaining weather record file field related data including weather archive metadata, weather file category metadata, weather file case metadata, weather file in-case file metadata and weather file management metadata;
the related data in the meteorological record file field also comprises queried ground files, high altitude files, radiation files, agricultural files, acid rain files, weather map files and station history leather files for automatic word list supplement;
The related data in the weather record file field also comprises data acquired based on the technical specifications of weather file business issued by the China weather office.
4. The method for constructing a knowledge graph of a weather record file according to claim 1, wherein,
by analyzing the requirement and the data of the weather record files, starting from the problem of difficult searching of the weather record files, defining the weather observation files, time, weather archives, weather record file files, administrative areas, file forming units and weather observation elements around three aspects of weather record file files, file formation and archive management, and extending the concepts of a management system, a responsible person, a production unit, weather observation specifications, weather observation instruments and a weather observation method based on the common query concept;
the value constraint defining each concept attribute and the attribute thereof comprises defining a paper file attribute, an electronic file attribute, an administrative region attribute, a weather observation station attribute, a weather observation event attribute, a time attribute, a weather observation liability person attribute, a weather observation standard attribute, a weather observation element attribute, a weather observation instrument attribute, a weather observation method attribute, an observation record attribute, a weather archive attribute, a archive formation unit attribute, a weather record archive attribute and a weather archive management regulation attribute.
5. The method for constructing a knowledge graph of a weather recording file according to claim 1, wherein the definition of the relationship of the body of the weather recording file is based on business analysis of the weather recording file, and the relationship among concepts is defined around the production, management and utilization of the weather recording file by using the weather recording file itself, i.e. "weather observation file", as a core, so as to establish the relationship among the data of the weather recording file.
6. The method for constructing a knowledge graph of a weather record file according to claim 1, wherein the correlation exists between different types of weather observation files at the same place and at the same time by examining the data of the weather record file;
different types of weather-observation files include: the most primitive observation records of the gas book and the self-recording paper, the observation data in the gas book read from the self-recording paper, the data in the gas meter read from the gas book, the month statistics calculated based on the day observation data, the data in the year report read from the month report, and the year statistics calculated based on the month statistics.
7. The method for constructing a knowledge graph of a weather recording archive of claim 1, wherein the knowledge graph of the weather recording archive comprises an intelligent retrieval module based on the archive itself, an intelligent retrieval module based on observation elements, and an intelligent retrieval module based on an observation station, wherein:
The intelligent retrieval module based on the archives is used for searching out the collection archives in the current archives in an associated manner based on the conceptual relationship and entity relationship of the knowledge graph of the meteorological record archives, associating each archives storage position, observation station, forming time, place and observation element, and establishing a relationship network for different entities related to the archives;
the intelligent retrieval module based on the observation elements is used for searching files in an associated mode according to a knowledge association relation network of the observation elements and based on the air pressure, air temperature, humidity and precipitation observation elements, the data characteristics of the file records are marked on the relation between the file files and the observation elements, and meanwhile observation times, observation persons, observation stations and files where the observation persons, the observation stations and the observation files are located are associated;
the intelligent retrieval module based on the observation station searches out image files, observation records, observers, station lengths, observation elements, observation instruments, change matters and observation field environment information of a certain period of the station or searches the station of the observation instrument used in the past according to the association relation network of the observation station to form a station leather information network.
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